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game-architect游戏架构师

Agent Skill

game-architect 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,864

周安装

411

GitHub Stars

1

下载量

3,288
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:game-architect(游戏架构师)
来源仓库:https://github.com/yuki001/game-architect
安装命令:
openclaw skills install game-architect
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install game-architect

简介

game-architect 专注于游戏系统架构设计,覆盖战斗、UI、叙事等多个模块。

  • 适用于规划大型游戏项目结构或优化现有系统间协作关系。
  • 提供模块化设计思路与跨领域整合方案,提升整体架构合理性。
  • 可直接在 OpenClaw 中调用,无需特殊配置即可辅助设计决策。
  • 推荐根据实际项目阶段选择性应用相关章节内容。

SKILL.md

name
game-architect
description
READ this skill when designing or planning any game system architecture — including combat, skills, AI, UI, multiplayer, narrative, or scene systems. Contains paradigm selection guides (DDD / Data-Driven / Prototype), system-specific design references, and mixing strategies. Works as a domain knowledge plugin alongside workflow skills (OpenSpec, SpecKit) or plan mode of an agent.

Game Architect Skill

Game architecture domain knowledge reference. Provides paradigm selection, system design references for game project architecture.

[!NOTE] This skill contains domain knowledge only, not a workflow. Pair it with a workflow skill (e.g., OpenSpec, SpecKit) or an agent's plan mode for structured design flow.

Usage Modes

With Workflow Skill (Recommended)

When used with a workflow skill (e.g., OpenSpec, SpecKit) or in the plan mode of an agent, this skill serves as a domain knowledge plugin:

  • During requirements/spec phases: Consult the Paradigm Selection Guide and System-Specific References to inform architectural decisions
  • During design/planning phases: Use the Reference Lookup Guide below to read relevant references/ documents

Standalone

A lightweight workflow-standalone.md is also available as a self-contained design pipeline if needed.

Knowledge Mode (Query)

When user requests to query knowledge for game architecture, this skill provides a reference lookup guide to relevant references/ documents based on the task.


Reference Lookup Guide

When designing game architecture, read the relevant references/ documents based on the task:

Architecture References

WhenRead
Always (high-level structure)references/macro-design.md
Always (core principles)references/principles.md
Requirement analysisreferences/requirements.md
Choosing DDD paradigmreferences/domain-driven-design.md
Choosing Data-Driven paradigmreferences/data-driven-design.md
Choosing Prototype paradigmreferences/prototype-design.md
Evolution & extensibility reviewreferences/evolution.md
Performance optimization neededreferences/performance-optimization.md
Multiplayer support neededreferences/system-multiplayer.md

For system-specific design, see the System-Specific References table below.

System-Specific References

System CategoryReference
Foundation & Core (Logs, Timers, Modules, Events, Resources, Audio, Input)references/system-foundation.md
Time & Logic Flow (Update Loops, Async, FSM, Command Queues, Controllers)references/system-time.md
Combat & Scene (Scene Graphs, Spatial Partitioning, ECS/EC, Loading)references/system-scene.md
UI & Modules (Modules Management, MVC/MVP/MVVM, UI Management, Data Binding, Reactive)references/system-ui.md
Skill System (Attribute, Skill, Buff)references/system-skill.md
Action Combat System (HitBox, Damage, Melee, Projectiles)references/system-action-combat.md
Narrative System (Dialogue, Cutscenes, Story Flow)references/system-narrative.md
Game AI System (Movement, Pathfinding, Decision Making, Tactical)references/system-game-ai.md
Multiplayer System (Client-Server, Sync Models, Distributed Server, AOI, Communication)references/system-multiplayer.md
Algorithm & Data Structures (Pathfinding, Search, Physics, Generic Solver)references/algorithm.md

Paradigm Selection Guide

ParadigmKeyPointApplicability ScopeExamplesReference
Domain-Driven Design (DDD)OOP & Entity FirstHigh Rule Complexity. <br> Rich Domain Concepts. <br> Many Distinct Entities.Core Combat Logic, Physics Interactions, Damage/Buff Rules, Complex AI Decision.references/domain-driven-design.md
Data-Driven DesignData Layer FirstHigh Content Complexity. <br> Flow Orchestration. <br> Simple Data Management.Content: Quests, Level Design.<br>Flow: Tutorial Flow, Skill Execution, Narrative.<br>Mgmt: Inventory, Shop, Mail, Leaderboard.references/data-driven-design.md
Use-Case Driven PrototypeUse-Case Implementation FirstRapid ValidationGame Jam, Core Mechanic Testing.references/prototype-design.md

Mixing Paradigms

Most projects mix paradigms:

  1. Macro Consistency: All modules follow the same Module Management Framework.
  2. Domain for Core Entities & Rules: Use DDD for systems with high rule complexity, rich domain concepts, and many distinct entities (e.g., Combat Actors, Damage Formulas, AI Decision).
  3. Data for Content, Flow & State: Use Data-Driven for expandable content (Quests, Level Design), flow orchestration (Tutorial, Skill Execution, Narrative), and simple data management (Inventory, Shop).
  4. Hybrid Paradigms:

- 4.1 Entities as Data: Domain Entities naturally hold both data (fields) and behavior (methods). Design entities to be serialization-friendly (use IDs, keep state as plain fields) so they serve both roles without a separate data layer. - 4.2 Flow + Domain: Use data-driven flow to orchestrate the sequence/pipeline, domain logic to handle rules at each step. E.g., Skill System: flow drives cast→channel→apply, domain handles damage calc and buff interactions. - 4.3 Separate Data/Domain Layers: Only when edit-time and runtime representations truly diverge. Use a Bake/Compile step to bridge them. E.g., visual node-graph editors, compiled assets.

  1. Paradigm Interchangeability: Many systems can be validly implemented with either paradigm. E.g., Actor inheritance hierarchy (Domain) ↔ ECS components + systems (Data-Driven); Buff objects with encapsulated rules (Domain) ↔ Tag + Effect data entries resolved by a generic pipeline (Data-Driven). See Selection Criteria table above for trade-off signals.
  2. Integration: Application Layer bridges different paradigms.

Selection Criteria

When both DDD and Data-Driven fit, use these signals:

SignalFavor DDDFavor Data-Driven
Entity interactionsComplex multi-entity rules (attacker × defender × buffs × environment)Mostly CRUD + display, few cross-entity rules
Behavior sourceVaries by entity type, hard to express as pure dataDriven by config tables, designer-authored content
Change frequencyRules change with game balance iterationsContent/flow changes far more often than logic
Performance profileAcceptable overhead for rich object graphsNeeds batch processing, cache-friendly layouts
NetworkingStateful objects acceptableFlat state snapshots preferred (sync, rollback)
Team workflowProgrammers own the logicDesigners need to iterate without code changes

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

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按下载量换算2,934

安全审计

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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